Data Science & AI Code-Alongs

In this code-along, Andrea Valenzuela, Computing Engineer at CERN, and Josep Ferrer Sanchez, Data Scientist at the Catalan Tourist Board, will walk you through building an AI system that can query your documents & data using LangChain & the OpenAI API.

In this code along, you'll learn how to use the OpenAI API and Python to get started fine-tuning GPT3.5.

In this code-along, you will be introduced to the basics of exploring new datasets. Using data on UK Premiership soccer results, you will use Python to calculate summary statistics and draw visualizations to generate insights.

In this session you'll learn how to get started with Chroma and perform Q&A on some documents using Llama 2, the RAG technique, and LlamaIndex.

In this webinar, you'll learn how to build your own diffuser model from scratch!

In this session, we cover the different evaluations that are useful for reducing hallucination and improving retrieval quality of LLMs.

In this code-along session, you will learn how to use Snowpark Python and SQL to perform data analysis in the Snowflake Data Cloud.

In this session, we take a step-by-step approach to fine-tune a Llama 2 model on a custom dataset.

In this webinar, you'll use MLflow to manage a machine learning experiment pipeline. The session will cover model evaluation, hyperparameter tuning, and MLOps strategies, using a London weather dataset.

In this session, you'll use ApertureDB to access the COCO dataset and run image recognition using Python.

In this session, you'll see how to use this tool to combine the text-writing skills of ChatGPT with the power of Python to perform some data analysis and machine-learning workflows.

In this session, you'll learn advanced prompting skills such as using prompt templates, testing the quality of your prompts, and working with images in prompts.